Biology subjects

The Milieu Interieur Consortium,

Publications and source records attributed to The Milieu Interieur Consortium,.

4 recordsLinked to original sources

bioRxiv2020

Stability and dynamics of the human gut microbiome and its association with systemic immune traits

Analysis of 1,363 deeply sequenced gut microbiome samples from 946 healthy donors of the Milieu Interieur cohort provides new opportunities to discover how the gut microbiome is associated with host factors and lifestyle parameters. Using a genome-based taxonomy to achieve higher resolution analysis, we found an enrichment of Prevotella species in males, and that bacterial profiles are dynamic across five decades of life (20-69), with Bacteroidota species consistently increased with age while Actinobacteriota species, including Bifidobacterium, decreased. Longitudinal sampling revealed short-term stability exceeds inter-individual differences; however, the degree of stability was variable between donors and influenced by their baseline community composition. We then integrated the microbiome results with systemic immunophenotypes to show that host/microbe associations discovered in animal models, such as T regulatory cells and short chain fatty acids, could be validated in human data. These results will enable personalized medicine approaches for microbial therapeutics and biomarkers.

microbiology↗

bioRxiv2019

Immune profiling in M. tuberculosis infection enables stratification of patients with active disease

Tuberculosis (TB) is caused by Mycobacterium tuberculosis (Mtb) infection and is a major public health problem with an estimated 1.7 billion persons infected worldwide. Clinical challenges in TB include the lack of a blood-based test for active disease, and the absence of prognostic biomarkers for early treatment response. Current blood based tests, such as QuantiFERON-TB Gold (QFT), are based on an IFN{gamma} readout following Mtb antigen stimulation. However, they do not distinguish active TB disease from asymptomatic Mtb infection. We hypothesized that the use of TruCulture, an improved immunomonitoring method for whole blood collection and immune stimulation, could improve the discrimination of active disease from latent Mtb infection. To test our hypothesis, we stimulated whole blood from active TB patients (before and after successful treatment), comparing them to asymptomatic latently infected individuals. Mtb-specific antigens (ESAT-6, CFP-10, TB7.7) and live bacillus Calmette-Guerin (BCG) were used for TruCulture stimulation conditions, with direct comparison to QFT. Protein analyses were performed on the culture supernatants using ELISA and Luminex multi-analyte profiling. TruCulture showed an ability to discriminate active TB cases from latent controls (p < 0.0001, AUC = 0.81, 95% CI: 0.69-0.93) as compared to QFT (p = 0.47 AUC = 0.56, 95% CI: 0.40-0.72), based on an IFN{gamma} readout after Mtb antigen stimulation. The stratification of the two groups could be further improved by using the Mtb Ag/BCG IFN{gamma} ratio response (p < 0.0001, AUC = 0.918, 95% CI: 0.84-0.98). We also identified additional cytokines that distinguished latent infection from TB disease; and show that the primary differences between the TruCulture and QFT systems were a result of higher levels of non-specific innate immune activation in QFT tubes, due to the lack of a buffering solution in the latter. We conclude that TruCulture offers a next-generation solution for whole blood stimulation and immunomonitoring with the possibility to discriminate active and latently infected persons.

immunology↗

bioRxiv2019

A Comprehensive Assessment of Demographic, Environmental and Host Genetic Associations with Gut Microbiome Diversity in Healthy Individuals

BackgroundThe gut microbiome is an important determinant of human health. Its composition has been shown to be influenced by multiple environmental factors and likely by host genetic variation. In the framework of the Milieu Interieur Consortium, a total of 1,000 healthy individuals of western European ancestry, with a 1:1 sex ratio and evenly stratified across five decades of life (age 20 - 69), were recruited. We generated 16S ribosomal RNA profiles from stool samples for 858 participants. We investigated genetic and non-genetic factors that contribute to individual differences in fecal microbiome composition. ResultsAmong 110 demographic, clinical and environmental factors, 11 were identified as significantly correlated with -diversity, {beta}-diversity or abundance of specific microbial communities in multivariable models. Age and blood alanine aminotransferase levels showed the strongest associations with microbiome diversity. In total, all non-genetic factors explained 16.4% of the variance. We then searched for associations between >5 million single nucleotide polymorphisms and the same indicators of fecal microbiome diversity, including the significant non-genetic factors as covariates. No genome-wide significant associations were identified after correction for multiple testing. A small fraction of previously reported associations between human genetic variants and specific taxa could be replicated in our cohort, while no replication was observed for any of the diversity metrics. ConclusionIn a well-characterized cohort of healthy individuals, we identified several non-genetic variables associated with fecal microbiome diversity. In contrast, host genetics only had a negligible influence. Demographic and environmental factors are thus the main contributors to fecal microbiome composition in healthy individuals.

genomics↗

bioRxiv2018

Genetic factors and age are the strongest predictors of humoral immune responses to common pathogens and vaccines

IntroductionHumoral immune responses to infectious agents or vaccination vary substantially among individuals, and many of the factors responsible for this variability remain to be defined. Current evidence suggests that human genetic variation influences (i) serum immunoglobulin levels, (ii) seroconversion rates, and (iii) intensity of antigen-specific immune responses. Here, we evaluate the impact of intrinsic (age and sex), environmental and genetic factors on the variability of humoral response to common pathogens and vaccines.\n\nMethodsWe characterized the serological response to 15 antigens from common human pathogens or vaccines, in an age- and sex-stratified cohort of 1,000 healthy individuals (Milieu Interieur cohort). Using clinical-grade serological assays, we measured total IgA, IgE, IgG and IgM levels, as well as qualitative (serostatus) and quantitative IgG responses to cytomegalovirus, Epstein-Barr virus, herpes simplex virus 1 & 2, varicella zoster virus, Helicobacter pylori, Toxoplasma gondii, influenza A virus, measles, mumps, rubella, and hepatitis B virus. Following genome-wide genotyping of single nucleotide polymorphisms and imputation, we examined associations between ~5 million genetic variants and antibody responses using single marker and gene burden tests.\n\nResults and discussionWe identified age and sex as important determinants of humoral response, with older individuals and women having higher rates of seropositivity for most antigens. Genome-wide association studies revealed significant associations between variants in the human leucocyte antigen (HLA) class II region on chromosome 6 and anti-EBV and anti-rubella IgG levels. We used HLA imputation to fine map these associations to amino acid variants in the peptide-binding groove of HLA-DR{beta}1 and HLA-DP{beta}1, respectively. We also observed significant associations for total IgA levels with two loci on chromosome 2 and with specific KIR-HLA combinations.\n\nConclusionsUsing extensive serological testing and genome-wide association analyses in a well-characterized cohort of healthy individuals, we demonstrate that age, sex and specific human genetic variants contribute to inter-individual variability in humoral response. By highlighting genes and pathways implicated in the normal antibody response to frequently encountered antigens, these findings provide a basis to better understand disease pathogenesis.

genomics↗